How can AI-driven analytics improve defect prediction and prioritization in functional testing?

AI-driven analytics in functional testing can improve defect prediction and prioritization by identifying patterns in historical test data. By analyzing trends and correlations, AI algorithms can predict potential defects and prioritize them based on historical patterns. This helps testing teams focus their efforts on critical areas, leading to more efficient defect management and improved overall software quality.